<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:content="http://purl.org/rss/1.0/modules/content/"><channel><title>Embeddings on Onur Baydaş</title><link>https://onurbaydas.com/en/tags/embeddings/</link><description>Recent content in Embeddings on Onur Baydaş</description><generator>Hugo</generator><language>en-us</language><lastBuildDate>Sat, 17 Oct 2026 12:15:22 +0300</lastBuildDate><atom:link href="https://onurbaydas.com/en/tags/embeddings/index.xml" rel="self" type="application/rss+xml"/><item><title>EmbeddingGemma 2: Open, Lightweight Multimodal Embedding Model</title><link>https://onurbaydas.com/en/news/2026-10-17-embedding-gemma-2-multimodal-model/</link><pubDate>Sat, 17 Oct 2026 12:15:22 +0300</pubDate><guid>https://onurbaydas.com/en/news/2026-10-17-embedding-gemma-2-multimodal-model/</guid><description>Google DeepMind announced EmbeddingGemma 2, a new open-source and lightweight multimodal embedding model. This model aims to represent different data types (text, image, etc.) in a single vector space.</description></item></channel></rss>